Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.
Explores data augmentation as a key regularization method in deep learning, covering techniques like translations, rotations, and artistic style transfer.
By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Explores the quality of Integrate-and-Fire models in computational neuroscience through comparisons with experimental data and mathematical predictions.
